| Abstract | Large scale deployment of additive manufacturing (AM) processes relies on part quality, specifically the presence of internai defects and part-to-part consistency. Sorne of the defects observed in finished parts have been associated with porosities in the powder feedstock used in AM processes including powder bed, laser cladding,and cold spray. Since the level of porosity in these powders is generally very low, standard characterization techniques, such as pycnometry and metallography with image analysis, are not well suited for quantification. This study presents a new approach combining high resolution X ray tomography with 3D image analysis to evaluate and quantify porosity in titanium powder feedstock. The effects of acquisition parameters and image analysis procedures on porosity quantification were investigated to validate the proposed method and assess its reliability. Data demonstrates that the proposed technique is sufficiently sensitive to differentiate powders with different porosity levels. |
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